Interactions between man and machine as the basis of economics at every level

1/20. In sales department, you notice that salespeople treat CRM as a control tool rather than a support tool. How do you change their attitude toward the technology?

Change the way of implementation: together with the team you match the tools to their work style, show their impact on customer relations and results.

Blindly ignore their resistance and enforce reporting without talking to them.

Show the concrete benefits of automating tasks and saving time.

Encourage use of the system, but don't offer training or support.

2/20. You're about to decide on a career specialty and are wondering what role machines will play in the future. How will you approach your career planning?

Build a career path based on your ability to collaborate with technology, strengthening your value as a human being in an automated world.

Assume that working with machines will limit your independence and creativity.

Choose a field where working with technology will allow you to operate more efficiently.

Focus on purely “human” occupations, avoiding technology industries.

3/20. Your company is piloting robotic assistants in a warehouse. What’s your approach to ensuring they support - not disrupt - staff?

Design shared workflows where both roles align.

Allow collaboration but limit robot adaptability.

Let robots work independently, without team contact.

Assign robots simple tasks without team coordination.

4/20. Your company is using AI to screen job applications. How do you ensure fairness in the process?

Regularly audit the system for biased patterns.

Let the AI make all decisions without review.

Manually check only the final shortlist.

Combine AI results with human review and inclusive criteria.

5/20. The influence of automation on labour markets is becoming more visible across industries. How should you interpret its growing role in employment?

Understand that automation redefines labor and demands a systemic shift in how we prepare the workforce.

Assume machines will always replace humans in routine tasks.

See automation simply as a threat to human workers and job security.

Recognize that automation changes the nature of jobs, requiring new skill sets.

6/20. You're preparing for a career in a data-driven industry. How should you think about your role in relation to machines?

Position yourself as a strategic partner to technology - interpreting data, applying human judgment, and ensuring ethical use.

Avoid technical tasks, assuming machines are better at them.

Rely fully on automation, minimizing your own decision-making.

Learn how to manage data tools to support better outcomes.

7/20. You’re part of a project team responsible for designing a new service involving predictive technologies. How will you approach building a relationship with the user?

Ignore his/her needs, because the technology “knows better” anyway.

Design the system according to the algorithm's predictions, without the audience's input.

Involve users from the beginning, testing different versions and constantly modifying the design according to real reception.

Consider the user's needs at the testing stage, but not during design.

8/20. You are considering the future of work in an economy based on human-machine interaction. How can you best understand your role in such a world?

Assume that machines will take over most of the responsibilities, so you will remain passive.

Begin to develop skills that complement the operation of technology.

Focus on tasks that machines can't yet do.

Define yourself as an active contributor to automated processes - a person who interacts with, interprets and gives direction to decisions made with machines.

9/20. In response to increasing automation, your organization is revising job descriptions to reflect the evolving balance between human and machine tasks. Employees are uncertain about how their roles will change and what skills they need to develop. As the HR director, how do you proceed to ensure clarity and engagement?

Collaborate with employees to co-create new role profiles that clearly define the synergy between human skills and technological capabilities.

Retain existing job descriptions and simply add “plus technology use” to each.

Eliminate all tasks from job descriptions that could potentially be automated.

Analyse current responsibilities to identify areas where machines can assist, and update descriptions accordingly.

10/20. A smart work scheduling system is being implemented by your company. After the first weeks of operation, there are signs that some employees feel they are being treated unfairly. You are responsible for assessing the situation and making further decisions. How do you react?

Involve workers in reviewing the system, organize joint tests, identify gaps and make transparent changes together with the technical team.

Assume that the system works according to the algorithm, so there is no need to explain anything to employees.

Explain workers that mistakes are possible, but you see no reason to make changes without the approval of the IT department.

Gather feedback from employees, analyze data from the system and suggest adjustments to schedules.

11/20. A manufacturing client is preparing to integrate collaborative robots (cobots) into their production line. The leadership team wants rapid adoption, but workers on the floor are unclear about how their responsibilities will change. There are concerns about safety, job security, and skill fit. You’re responsible for guiding the rollout process. How do you proceed?

Train workers to cooperate with cobots using basic safety routines.

Design adaptive workflows where cobots support human skills, involve staff in planning, and include shared performance goals.

Install cobots immediately and let staff adjust on their own.

Recommend limiting cobot use to a single repetitive task.

12/20. As the head of training at a logistics firm, you aim to increase the adoption of Internet of Things (IoT) systems among warehouse staff. Workers are expressing confusion and resistance toward interpreting and utilizing sensor data effectively. What strategy do you employ to facilitate understanding and acceptance?

Distribute written manuals and provide a basic orientation session.

Allow workers to adapt to the new system through trial and error without formal guidance.

Develop an interactive training program featuring real-time data simulations, role-specific use cases, and continuous performance tracking to build competence and confidence in using the IoT systems.

Conduct live demonstrations followed by Q&A sessions to address immediate concerns.

13/20. Your logistics company is in the process of rolling out an AI-powered route optimization system for drivers. While the technology promises faster deliveries and fuel savings, several experienced drivers question the accuracy of the suggestions and feel their local knowledge is being ignored. You’ve been asked to increase trust in the system while ensuring efficiency gains. How do you proceed?

Explain that it will probably get better over time and hope for adoption.

Tell drivers to follow the system blindly and stop questioning it.

Facilitate hands-on training where drivers test and evaluate route options, give feedback, and adjust systems collaboratively.

Provide workshops comparing system recommendations with real-time outcomes.

14/20. A city transport agency is considering automating key functions of its public bus network, including navigation, scheduling, and dispatch operations. The goal is to improve route efficiency, reduce delays, and minimize human error. However, many bus operators and dispatch staff worry that their expertise is being undervalued - and that automation could lead to job losses. Union representatives are requesting clarity about future roles, and the public is raising concerns about safety, especially in complex urban environments. You’ve been brought in as a consultant to help shape the strategy in a way that embraces innovation while preserving human value and trust. What do you propose?

Retrain operators to oversee automated systems from centralized control rooms, focusing on technical monitoring and system reliability.

Suggest replacing all operators with automation as a cost-saving measure, assuming full trust in the system's performance.

Keep operators employed only for rare emergency interventions, minimizing their active involvement in daily operations.

Redesign operator roles to include real-time data management, direct communication with passengers, and rapid response to unexpected events or system errors.

15/20. Your retail company is transitioning from manual inventory checks to an advanced system utilizing smart sensors and AI algorithms. While this promises real-time stock updates and improved supply chain efficiency, many employees express concern about the reliability of the technology and fear that their roles may become redundant. As the operations manager, how do you address these concerns and facilitate a smooth transition?

Assign only tech-savvy employees to interact with the new technology.

Provide comprehensive training focused on interpreting and responding to the system’s outputs.

Avoid discussing the new system to prevent alarming staff.

Redefine job roles to emphasize human oversight, critical decision-making, and handling exceptions that the AI system may not address, positioning employees as essential partners in the technology integration.

16/20. The HR department in your company is deploying robotic process automation (RPA) to handle administrative tasks like leave approvals and performance tracking. While this should free up time for more meaningful work, many employees are worried about surveillance and losing control over their own data. You’ve been asked to introduce the system in a way that reduces fear and builds understanding. What’s your approach?

Send out a mass email announcing the change without context.

Organize workshops explaining how it works, involve staff in process design, and ensure transparent communication from day one.

Hold a general briefing to explain its function and benefits.

Launch it quietly and hope no one notices.

17/20. You want to prepare your students or employees for the automated economy. Which approach best supports long-term employability?

Focus on teaching discipline-specific theory, assuming adaptability can be learned later in the workplace.

Develop a balanced curriculum that combines AI/data literacy, critical thinking, creativity, ethical reasoning and continuous learning skills.

Prioritize manual skills to preserve traditional employment sectors in case automation fails.

Limit digital education to basic computer use to avoid overwhelming learners with complex technologies.

18/20. A nation introduces laws to regulate AI and robotics across sectors. Effective AI regulation should aim to:

Introduce protectionist policies that limit foreign AI technologies to preserve national industries and employment.

Establish a regulatory framework that encourages innovation while ensuring transparency, data protection, algorithmic accountability and protection of workers’ rights.

Delegate AI governance primarily to industry leaders, assuming market forces will organically resolve ethical challenges.

Suspend AI deployment until all long-term ethical consequences are scientifically proven and universally agreed upon.

19/20. A company increases profits through automation, but wages remain unchanged for employees. What is the most sustainable long-term response?

Introduce profit-sharing mechanisms, re-invest in employee reskilling and apply fair taxation models for automation-generated wealth to reduce inequality.

Introduce identical wage increases across all roles to maintain harmony, regardless of productivity or skill levels.

Gradually freeze further automation plans until employee satisfaction improves organically over time.

Focus on maximizing shareholder returns by outsourcing non-automated roles to lower-cost regions, delaying wage reform.

20/20. Urban planners want to use AI and IoT to create a smart city. For long-term sustainability, what should be prioritized?

Replace traditional public service roles with automated systems as a cost-saving priority, regardless of public sentiment.

Centralize citizen data collection to optimize services, while ethical decisions are postponed until systems are fully deployed.

Integrate privacy-by-design principles, establish transparent data governance and ensure citizen participation in decision-making.

Consult only technical experts, assuming civic participation would delay innovation.

Your result: /100

You have achieved a Low Readiness Index. Your approach to human–machine collaboration remains at an early stage. You often rely on automation without fully integrating your own judgment or critical interpretation of data. Ethical safeguards, bias prevention, and user participation in design are often missing, which can lead to mistrust and reduced adoption. In several areas, you use technology as a replacement rather than as a partner to human skills, overlooking opportunities for shared responsibility models and transparent communication. To improve, you should follow these steps.

Steps to be taken to improve your Readiness Index:

Prioritise embedding human oversight in all tech-driven processes.
Create hybrid workflows where machines enhance but do not dictate decisions.
Involve diverse stakeholders in design and testing.
Take targeted training to build confidence in interpreting and challenging AI outputs.
Strengthen communication to clearly explain how decisions are made and build user trust.

You have achieved a Moderate Readiness Index. Many of your responses indicate an awareness of the value of hybrid human–machine models, ethical reviews, and user inclusion, but these are not consistently selected. In some cases, you implement automation decisions without adequate feedback loops or cross-departmental input, and you use data without sufficient critical analysis. To strengthen your readiness, you should follow the steps below.

Steps to be taken to improve your Readiness Index:

Make ethics and bias audits standard practice.
Involve diverse teams early in project design.
Ensure training goes beyond technical operation to include strategic use of technology.
Introduce scenario-based simulations where teams jointly interpret AI outputs, compare them with human insights, and adjust processes accordingly.

You have achieved a High Readiness Index. Your results indicate strong ability to combine human insight with advanced technologies in a balanced and ethical way. You show confidence in interpreting data critically, recognising when human judgment should guide or adjust automated outputs, and maintaining transparency in decision-making. You also demonstrate skill in engaging stakeholders, designing solutions with user needs in mind, and integrating ethics into everyday practice. The scenario choices suggest you adapt quickly to change, approach automation as a partner rather than a replacement, and can manage both the technical and human dimensions of Industry 5.0. This readiness level confirms you are well prepared to operate in environments where collaboration between people and intelligent systems is central. To refine your skills even further, you should follow these steps:

Continue testing advanced personalisation in intelligent systems.
Explore multi-user collaboration tools.
Share best practices to strengthen wider readiness.

EQF level alignment

According to your results, your current competence level can be estimated as %EQF%.

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Interactions between man and machine as the basis of economics at every level